reverse engineering chinese censorshipchinese censorship the largest selective suppression of human...
TRANSCRIPT
Reverse Engineering Chinese Censorship1
Gary King2
Institute for Quantitative Social ScienceHarvard University
(Talk at Wesleyan University, 3/6/2014)
1Based on joint work with Jennifer Pan and Molly Roberts2GaryKing.org
1/29
Papers
An Observational Study:
How Censorship in China Allows Government Criticism butSilences Collective Expression (American Political Science Review, May 2013)
Experimental and Participatory Studies:
A Randomized Experimental Study of Censorship in China
Copies at GaryKing.org
2/29
Chinese Censorship
The largest selective suppression of human expression in history
:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state
2 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state
2 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state
2 Stop collective action
Right
Either or both could be right or wrong.
(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action
Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Censorship
The largest selective suppression of human expression in history:
implemented manually,
by ≈ 200, 000 workers,
located in government and inside social media firms
Theories of the Goal of Censorship
1 Stop criticism of the state Wrong
2 Stop collective action Right
Either or both could be right or wrong.
(They also censor 2 other smaller categories we’ll talk about)
Benefit
?
Huge
Cost
Huge
None
3/29
Chinese Social Media: Fractured over 1,400+ sites
4/29
Chinese Social Media: Fractured over 1,400+ sites
hi.baidu 12%
bbs.voc.com.cn 5%
bbs.m4.cn 4%tianya 3%bbs.beijingww.com 2%
Share of Posts in Our Analysis by Internet Content Provider (ICP)
(Plus 59% from Sina Blog)5/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears
(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)
Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Observational Study
Collect 3,674,698 social media posts in 85 topic areas over 6 months
Random sample: 127,283
(Repeat design; Total analyzed: 11,382,221)
For each post (on a timeline in one of 85 content areas):
Download content the instant it appears(Carefully) revisit each later to determine if it was censored (fromcomputers all over the world)Use computer-assisted methods of text analysis (some existing, somenew, all adapted to Chinese)
6/29
Censorship is not Ambiguous: Example Error Page
7/29
Censorship is not Ambiguous: BBS Error Page
8/29
The Censors are Fast; Our Automated Methods are Faster
Days Until Censorship, Shanghai Subway Analysis
Days After Post Was Written
Num
ber C
enso
red
0 1 2 3 4 5 6 7
050
100
150
200
250
9/29
The Censors are Fast; Our Automated Methods are FasterExample: Shanghai Subway Crash
Days Until Censorship, Shanghai Subway Analysis
Days After Post Was Written
Num
ber C
enso
red
0 1 2 3 4 5 6 7
050
100
150
200
250
9/29
The Censors are Fast; Our Automated Methods are FasterExample: Shanghai Subway Crash
Days Until Censorship, Shanghai Subway Analysis
Days After Post Was Written
Num
ber C
enso
red
0 1 2 3 4 5 6 7
050
100
150
200
250
9/29
For 2 Unusual Topics: Constant Censorship Effort
05
1015
Count
Jan Mar Apr May Jun
Count PublishedCount Censored
Count PublishedCount Censored
010
2030
4050
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored
Students Throw Shoes at
Fang BinXing
Pornography Criticism of the Censors
10/29
For 2 Unusual Topics: Constant Censorship Effort0
510
15
Count
Jan Mar Apr May Jun
Count PublishedCount Censored
Count PublishedCount Censored
010
2030
4050
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored
Students Throw Shoes at
Fang BinXing
Pornography Criticism of the Censors
10/29
All other topics: Censorship & Post Volume are “Bursty”
010
2030
4050
6070
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst
(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
All other topics: Censorship & Post Volume are “Bursty”0
1020
3040
5060
70
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored Riots in
Zengcheng
Unit of analysis:
volume burst(≈ 3 SDs greaterthan baseline volume)
We monitored 85 topicareas (Jan–July 2011)
Found 87 volume burstsin total
Identified real worldevents associated witheach burst
Our hypothesis: The government censors all posts in volume burstsassociated with events with collective action potential (regardless of howcritical or supportive of the state)
11/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship
-0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 1: Post Volume
Begin with our 87 volume bursts in 85 topics areas
For each burst, calculate change in % censorship inside to outsideeach volume burst within topic areas – censorship magnitude
If goal of censorship is to stop collective action, we expect:
1 On average, % censoredshould increase duringvolume bursts
2 Some bursts (associatedwith politically relevantevents) should havemuch higher censorship -0.2 0.0 0.2 0.4 0.6 0.8
01
23
45
Censorship Magnitude
Density
12/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internet
individuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;
topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.
(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
Observational Test 2: The Events Generating the Bursts
Event classification (each category can be +, −, or neutral commentsabout the state)
1 Collective Action Potential
protest or organized crowd formation outside the Internetindividuals who have organized or incited collective action on theground in the past;topics related to nationalism or nationalist sentiment that have incitedprotest or collective action in the past.(Inter-coder reliability: 98.9%)
2 Criticism of censors
3 Pornography
4 (Other) News
5 Government Policies
13/29
What Types of Events Are Censored?
Censorship Magnitude
Density
02
46
810
12
-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
Collective ActionCriticism of CensorsPornography
PolicyNews
14/29
What Types of Events Are Censored?
Censorship Magnitude
Popular Book Published in Audio FormatDisney Announced Theme ParkEPA Issues New Rules on LeadChinese Solar Company Announces EarningsChina Puts Nuclear Program on HoldGov't Increases Power PricesJon Hunstman Steps Down as Ambassador to ChinaNews About Iran Nuclear ProgramIndoor Smoking Ban Takes EffectPopular Video Game ReleasedEducation Reform for Migrant ChildrenFood Prices RiseU.S. Military Intervention in Libya
Censorship Magnitude
New Laws on Fifty Cent PartyRush to Buy Salt After Earthquake
Students Throw Shoes at Fang BinXingFuzhou Bombing
Localized Advocacy for Environment LotteryGoogle is Hacked
Collective Anger At Lead Poisoning in JiangsuAi Weiwei Arrested
Pornography Mentioning Popular BookZengcheng Protests
Baidu Copyright LawsuitPornography Disguised as News
Protests in Inner Mongolia
PoliciesNews
Collective ActionCriticism of CensorsPornography
-0.2 0 0.1 0.3 0.5 0.7
14/29
Censoring Collective Action: Ai Weiwei’s Arrest
010
2030
40
Count
Jan Mar Apr May Jun Jul
Count PublishedCount Censored
Ai Weiwei arrested
15/29
Censoring Collective Action: Protests in Inner Mongolia
05
1015
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored
Protests in Inner Mongolia
16/29
Low Censorship on One Child Policy
010
2030
40
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored
Speculation of
Policy Reversal at NPC
17/29
Low Censorship on News: Power Prices
010
2030
4050
6070
Count
Jan Feb Mar Apr May Jun Jul
Count PublishedCount Censored
Power shortages Gov't raises power prices
to curb demand
18/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation set
ReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each category
Quantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
Observational Test 3: Content of Posts
We adapted “ReadMe” (Hopkins-King) methodology to the content ofcensored posts in Chinese
Standardize encoding of Chinese text
Eliminate punctuation and stop words
Experiment with segmenting characters into words
Calculate the quantity of interest (% censored by category)
Code a validation setReadMe estimates: % of posts in each categoryQuantity of interest: % of posts censored in a category
P(Censored |Category) =P(Category |Censored)P(Censored)
P(Category)
19/29
“ReadMe” Algorithm Validated in Chinese
20/29
“ReadMe” Algorithm Validated in ChineseExample: Labor Strikes, 2010 (Training set: 100; Test set: 900)
20/29
“ReadMe” Algorithm Validated in ChineseExample: Labor Strikes, 2010 (Training set: 100; Test set: 900)
0.0
0.2
0.4
0.6
ReadMe Results for Chinese Sampled, Not Segmented
Probability
Facts Supporting Employers
Facts Supporting Workers
Opinions Supporting Workers
Opinions Supporting Employers or Irrelevant
20/29
“ReadMe” Algorithm Validated in ChineseExample: Labor Strikes, 2010 (Training set: 100; Test set: 900)
0.0
0.2
0.4
0.6
ReadMe Results for Chinese Sampled, Not Segmented
Probability
Facts Supporting Employers
Facts Supporting Workers
Opinions Supporting Workers
Opinions Supporting Employers or Irrelevant
ReadMeTrue
20/29
Uncensored: Non-Collective Action Posts (that Support orOppose the State)
Per
cent
Cen
sore
d
0.0
0.2
0.4
0.6
0.8
1.0
Criticize Support Criticize Support Criticize Support
One Child Policy Corruption Policy Food Prices Rise
21/29
Uncensored: Non-Collective Action Posts (that Support orOppose the State)
Per
cent
Cen
sore
d
0.0
0.2
0.4
0.6
0.8
1.0
Criticize Support Criticize Support Criticize Support
One Child Policy Corruption Policy Food Prices Rise
21/29
Censored: Collective Action Posts (that Support orCriticize the State)
Per
cent
Cen
sore
d
0.0
0.2
0.4
0.6
0.8
1.0
Criticize Support Criticize Support Criticize Support
Ai Weiwei Inner MongoliaFuzhou Bombing
22/29
Censored: Collective Action Posts (that Support orCriticize the State)
Per
cent
Cen
sore
d
0.0
0.2
0.4
0.6
0.8
1.0
Criticize Support Criticize Support Criticize Support
Ai Weiwei Inner MongoliaFuzhou Bombing
22/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)
Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)
Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)
Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to type
Checked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)
Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentives
Procedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in China
Bought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselves
To learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Additional Research Designs
1 Randomized Experiment (for causal inferences)
Selected 100 top social media sites (∼87% of blogs, >500M Users,geographically diverse)Created 2 accounts on each (from inside China all over the country)Wrote 1,200 unique social media posts (CA/not CA, Pro/Anti)Submitted posts randomly assigned to typeChecked on censorship (from computers in many countries)
2 Participatory Study (for descriptive inferences)
Current method of learning how they censor: ask (carefully!)Our goal: change our sources’ incentivesProcedure: create our own social media website in ChinaBought URL; contracted with firms for servers & software; posted andcensored ourselvesTo learn: we tried every software option, read the documentation, andcalled customer support(!)
23/29
Mechanisms of Censorship
24/29
Mechanisms of Censorship
24/29
Mechanisms of Censorship
24/29
Mechanisms of Censorship
24/29
Posts For v. Against Government: Zero Causal Effect
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
PanxuProtest
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
●
YellowLightFines
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
●
YellowLightFines
●
StockMarketCrash
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
●
YellowLightFines
●
StockMarketCrash
●
Investigationof Sichuan
ViceGovernor
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
●
YellowLightFines
●
StockMarketCrash
●
Investigationof Sichuan
ViceGovernor
●
GenderImbalance
25/29
Posts For v. Against Government: Zero Causal Effect
● ●
−0.
50.
00.
51.
0
Cen
sors
hip
Diff
eren
ce (
Pro
− A
nti)
●
TibetanSelf−
Immolations
●
PanxuProtest
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
●
CorruptionPolicy
●
EliminateGoldenWeek
●
RentalTax
●
YellowLightFines
●
StockMarketCrash
●
Investigationof Sichuan
ViceGovernor
●
GenderImbalance
●
Li TianyiScandal
25/29
Collective Action Events: Large Causal Effect
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
PanxuProtest
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
●
PanxuProtest
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
●
PanxuProtest
●
TibetanSelf−
Immolations
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
26/29
Collective Action Events: Large Causal Effect
● ●0.0
0.1
0.2
0.3
0.4
0.5
Cen
sors
hip
Diff
eren
ce (
CA
Eve
nt −
Non
−C
A E
vent
)
●
PanxuProtest
●
TibetanSelf−
Immolations
●
Ai WeiweiAlbum
●
Protestsin
Xinjiang
26/29
Censorship to Preempt Collective Action: Ai Weiwei’sArrest
Mar 19 Mar 29 Apr 08 Apr 18
0.0
0.2
0.4
0.6
0.8
1.0
2011
% o
f Pos
ts C
enso
red
Actual %censorship
Predicted %censor trend basedon 3/19−3/29 data
Mar. 29,5 days prior
Apr. 3,Ai Weiwei Arrested
Placebo Test: Mostextreme of all effects
27/29
Censorship to Preempt Collective Action: Ai Weiwei’sArrest
Mar 19 Mar 29 Apr 08 Apr 18
0.0
0.2
0.4
0.6
0.8
1.0
2011
% o
f Pos
ts C
enso
red
Actual %censorship
Predicted %censor trend basedon 3/19−3/29 data
Mar. 29,5 days prior
Apr. 3,Ai Weiwei Arrested
Placebo Test: Mostextreme of all effects
27/29
Censorship to Preempt Collective Action: Ai Weiwei’sArrest
Mar 19 Mar 29 Apr 08 Apr 18
0.0
0.2
0.4
0.6
0.8
1.0
2011
% o
f Pos
ts C
enso
red
Actual %censorship
Predicted %censor trend basedon 3/19−3/29 data
Mar. 29,5 days prior
Apr. 3,Ai Weiwei Arrested
Placebo Test:
Mostextreme of all effects
27/29
Censorship to Preempt Collective Action: Ai Weiwei’sArrest
Mar 19 Mar 29 Apr 08 Apr 18
0.0
0.2
0.4
0.6
0.8
1.0
2011
% o
f Pos
ts C
enso
red
Actual %censorship
Predicted %censor trend basedon 3/19−3/29 data
Mar. 29,5 days prior
Apr. 3,Ai Weiwei Arrested
Placebo Test: Mostextreme of all effects
27/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticism
Reveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, Participatory
Automated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)
Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activities
Reveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silent
Possibly applicable to other countries
28/29
Concluding Remarks
Chinese people’s speech: Individually Free, Collectively in Chains
The Chinese Censorship Program:
Stops collective action, not criticismReveals government intentions; predicts actions
Our methodology:
Observational, Experimental, ParticipatoryAutomated text analysis methods validated in Chinese (withouttranslation)Enables continuous time measurement of Chinese governmentcensorship activitiesReveals information about state action when traditional media is silentPossibly applicable to other countries
28/29
For more information
GaryKing.org
j.mp/JenPan
j.mp/MollyRoberts
29/29
Appendix
30/29
Predicting the South China Sea Peace Agreement
Jun 12 Jun 22 Jul 02
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2011
% o
f Pos
ts C
enso
red
Predicted % censortrend basedon 6/10−6/20 data
Actual %censorship
Jun. 20,5 days prior
Jun. 25,PeaceAgreement
Placebo Test: Mostextreme of all effects
31/29
Predicting the South China Sea Peace Agreement
Jun 12 Jun 22 Jul 02
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2011
% o
f Pos
ts C
enso
red
Predicted % censortrend basedon 6/10−6/20 data
Actual %censorship
Jun. 20,5 days prior
Jun. 25,PeaceAgreement
Placebo Test: Mostextreme of all effects
31/29
Predicting the South China Sea Peace Agreement
Jun 12 Jun 22 Jul 02
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2011
% o
f Pos
ts C
enso
red
Predicted % censortrend basedon 6/10−6/20 data
Actual %censorship
Jun. 20,5 days prior
Jun. 25,PeaceAgreement
Placebo Test:
Mostextreme of all effects
31/29
Predicting the South China Sea Peace Agreement
Jun 12 Jun 22 Jul 02
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
2011
% o
f Pos
ts C
enso
red
Predicted % censortrend basedon 6/10−6/20 data
Actual %censorship
Jun. 20,5 days prior
Jun. 25,PeaceAgreement
Placebo Test: Mostextreme of all effects
31/29
Censorship Pre-empting Collective Action: Wang Lijun’sDemotion
Jan 23 Jan 30 Feb 06 Feb 13
−0.
20.
00.
20.
40.
60.
81.
0
2012
% o
f Pos
ts C
enso
red
Jan. 28,5 days prior
Feb. 2,Wang Lijundemoted
Actual %censorship
Predicted %censor trend basedon 1/18−1/28 data
Placebo Test: Mostextreme of all effects
32/29
Censorship Pre-empting Collective Action: Wang Lijun’sDemotion
Jan 23 Jan 30 Feb 06 Feb 13
−0.
20.
00.
20.
40.
60.
81.
0
2012
% o
f Pos
ts C
enso
red
Jan. 28,5 days prior
Feb. 2,Wang Lijundemoted
Actual %censorship
Predicted %censor trend basedon 1/18−1/28 data
Placebo Test: Mostextreme of all effects
32/29
Censorship Pre-empting Collective Action: Wang Lijun’sDemotion
Jan 23 Jan 30 Feb 06 Feb 13
−0.
20.
00.
20.
40.
60.
81.
0
2012
% o
f Pos
ts C
enso
red
Jan. 28,5 days prior
Feb. 2,Wang Lijundemoted
Actual %censorship
Predicted %censor trend basedon 1/18−1/28 data
Placebo Test:
Mostextreme of all effects
32/29
Censorship Pre-empting Collective Action: Wang Lijun’sDemotion
Jan 23 Jan 30 Feb 06 Feb 13
−0.
20.
00.
20.
40.
60.
81.
0
2012
% o
f Pos
ts C
enso
red
Jan. 28,5 days prior
Feb. 2,Wang Lijundemoted
Actual %censorship
Predicted %censor trend basedon 1/18−1/28 data
Placebo Test: Mostextreme of all effects
32/29
Uncensored Posts (w/o Collective Action Potential)Critical of the State
33/29
Uncensored Posts (w/o Collective Action Potential)Critical of the State
33/29
Uncensored Posts (w/o Collective Action Potential)Critical of the State
This is a city government [Yulin City,Shaanxi] that treats life with contempt, thisis government officials run amuck, a citygovernment without justice, a city govern-ment that delights in that which is vul-gar, a place where officials all have mis-tresses, a city government that is shamelesswith greed, a government that trades dig-nity for power, a government without hu-manity, a government that has no limits onimmorality, a government that goes back onits word, a government that treats kindnesswith ingratitude, a government that caresnothing for posterity. . .
33/29
Censored Post (with Collective Action Potential)Supporting the State
34/29
Censored Post (with Collective Action Potential)Supporting the State
34/29
Censored Post (with Collective Action Potential)Supporting the State
The bombing led not only to the tragedy ofhis death but the death of many governmentworkers. Even if we can verify what QianMingqi said on Weibo that the building de-molition caused a great deal of personal dam-age, we should still condemn his extreme actof retribution. . . . The government has con-tinually put forth measures and laws to pro-tect the interests of citizens in building de-molition. And the media has called attentionto the plight of those experiencing housingdemolition. The rate at which compensationfor housing demolition has increased exceedsinflation. In many places, this compensationcan change the fate of an entire family.
34/29